Analysis and Quantification of the Mitochondrial-ER Lipidome.

Mitochondria are vital organelles essential for cellular functions, but their lipid composition and response to stressors are not fully understood. Recent advancements in lipidomics reveal insights into lipid functions, especially their roles in metabolic perturbations and diseases. Previous methods have focused on the protein composition of mitochondria and mitochondrial-associated membranes. The advantage of our technique is that it combines organelle isolation with targeted lipidomics, offering new insights into the composition and dynamics of these organelles in pathological conditions. We developed a mitochondria isolation protocol for L6 myotubes, enabling lipidomics analysis of specific organelles without interference from other cellular compartments. This approach offers a unique opportunity to dissect lipid dynamics within mitochondria and their associated ER compartments under cellular stress. Key features • Analysis and quantification of lipids in mitochondria-ER fraction through liquid chromatography-tandem mass spectrometry-based lipidomics (LC-MS/MS lipidomics). • LC-MS/MS lipidomics provide precise and unbiased information on the lipid composition in in vitro systems. • LC-MS/MS lipidomics facilitates the identification of lipid signatures in mammalian cells.

Deletion of miPEP in adipocytes protects against obesity and insulin resistance by boosting muscle metabolism.

Mitochondria facilitate thousands of biochemical reactions, covering a broad spectrum of anabolic and catabolic processes. Here we demonstrate that the adipocyte mitochondrial proteome is markedly altered across multiple models of insulin resistance and reveal a consistent decrease in the level of the mitochondrial processing peptidase miPEP. OBJECTIVE: To determine the role of miPEP in insulin resistance. METHODS: To experimentally test this observation, we generated adipocyte-specific miPEP knockout mice to interrogate its role in the aetiology of insulin resistance. RESULTS: We observed a strong phenotype characterised by enhanced insulin sensitivity and reduced adiposity, despite normal food intake and physical activity. Strikingly, these phenotypes vanished when mice were housed at thermoneutrality, suggesting that metabolic protection conferred by miPEP deletion hinges upon a thermoregulatory process. Tissue specific analysis of miPEP deficient mice revealed an increment in muscle metabolism, and upregulation of the protein FBP2 that is involved in ATP hydrolysis in the gluconeogenic pathway. CONCLUSION: These findings suggest that miPEP deletion initiates a compensatory increase in skeletal muscle metabolism acting as a protective mechanism against diet-induced obesity and insulin resistance.

Multi-targeted loss of the antigen presentation molecule MR1 during HSV-1 and HSV-2 infection.

The major histocompatibility complex (MHC), Class-I-related (MR1) molecule presents microbiome-synthesized metabolites to Mucosal-associated invariant T (MAIT) cells, present at sites of herpes simplex virus (HSV) infection. During HSV type 1 (HSV-1) infection there is a profound and rapid loss of MR1, in part due to expression of unique short 3 protein. Here we show that virion host shutoff RNase protein downregulates MR1 protein, through loss of MR1 transcripts. Furthermore, a third viral protein, infected cell protein 22, also downregulates MR1, but not classical MHC-I molecules. This occurs early in the MR1 trafficking pathway through proteasomal degradation. Finally, HSV-2 infection results in the loss of MR1 transcripts, and intracellular and surface MR1 protein, comparable to that seen during HSV-1 infection. Thus HSV coordinates a multifaceted attack on the MR1 antigen presentation pathway, potentially protecting infected cells from MAIT cell T cell receptor-mediated detection at sites of primary infection and reactivation.

Dual Tracer Test to Measure Tissue-Specific Insulin Action in Individual Mice Identifies In Vivo Insulin Resistance Without Fasting Hyperinsulinemia.

The ability of metabolically active tissues to increase glucose uptake in response to insulin is critical to whole-body glucose homeostasis. This report describes the Dual Tracer Test, a robust method involving sequential retro-orbital injection of [14C]2-deoxyglucose ([14C]2DG) alone, followed 40 min later by injection of [3H]2DG with a maximal dose of insulin to quantify both basal and insulin-stimulated 2DG uptake in the same mouse. The collection of both basal and insulin-stimulated measures from a single animal is imperative for generating high-quality data since differences in insulin action may be misinterpreted mechanistically if basal glucose uptake is not accounted for. The approach was validated in a classic diet-induced model of insulin resistance and a novel transgenic mouse with reduced GLUT4 expression that, despite ubiquitous peripheral insulin resistance, did not exhibit fasting hyperinsulinemia. This suggests that reduced insulin-stimulated glucose disposal is not a primary contributor to chronic hyperinsulinemia. The Dual Tracer Test offers a technically simple assay that enables the study of insulin action in many tissues simultaneously. By administering two tracers and accounting for both basal and insulin-stimulated glucose transport, this assay halves the required sample size for studies in inbred mice and demonstrates increased statistical power to detect insulin resistance, relative to other established approaches, using a single tracer. The Dual Tracer Test is a valuable addition to the metabolic phenotyping toolbox.

Mitochondrial electron transport chain, ceramide, and coenzyme Q are linked in a pathway that drives insulin resistance in skeletal muscle.

Insulin resistance (IR) is a complex metabolic disorder that underlies several human diseases, including type 2 diabetes and cardiovascular disease. Despite extensive research, the precise mechanisms underlying IR development remain poorly understood. Previously we showed that deficiency of coenzyme Q (CoQ) is necessary and sufficient for IR in adipocytes and skeletal muscle (Fazakerley et al., 2018). Here, we provide new insights into the mechanistic connections between cellular alterations associated with IR, including increased ceramides, CoQ deficiency, mitochondrial dysfunction, and oxidative stress. We demonstrate that elevated levels of ceramide in the mitochondria of skeletal muscle cells result in CoQ depletion and loss of mitochondrial respiratory chain components, leading to mitochondrial dysfunction and IR. Further, decreasing mitochondrial ceramide levels in vitro and in animal models (mice, C57BL/6J) (under chow and high-fat diet) increased CoQ levels and was protective against IR. CoQ supplementation also rescued ceramide-associated IR. Examination of the mitochondrial proteome from human muscle biopsies revealed a strong correlation between the respirasome system and mitochondrial ceramide as key determinants of insulin sensitivity. Our findings highlight the mitochondrial ceramide-CoQ-respiratory chain nexus as a potential foundation of an IR pathway that may also play a critical role in other conditions associated with ceramide accumulation and mitochondrial dysfunction, such as heart failure, cancer, and aging. These insights may have important clinical implications for the development of novel therapeutic strategies for the treatment of IR and related metabolic disorders.

SnapKin: a snapshot deep learning ensemble for kinase-substrate prediction from phosphoproteomics data.

A major challenge in mass spectrometry-based phosphoproteomics lies in identifying the substrates of kinases, as currently only a small fraction of substrates identified can be confidently linked with a known kinase. Machine learning techniques are promising approaches for leveraging large-scale phosphoproteomics data to computationally predict substrates of kinases. However, the small number of experimentally validated kinase substrates (true positive) and the high data noise in many phosphoproteomics datasets together limit their applicability and utility. Here, we aim to develop advanced kinase-substrate prediction methods to address these challenges. Using a collection of seven large phosphoproteomics datasets, and both traditional and deep learning models, we first demonstrate that a 'pseudo-positive' learning strategy for alleviating small sample size is effective at improving model predictive performance. We next show that a data resampling-based ensemble learning strategy is useful for improving model stability while further enhancing prediction. Lastly, we introduce an ensemble deep learning model ('SnapKin') by incorporating the above two learning strategies into a 'snapshot' ensemble learning algorithm. We propose SnapKin, an ensemble deep learning method, for predicting substrates of kinases from large-scale phosphoproteomics data. We demonstrate that SnapKin consistently outperforms existing methods in kinase-substrate prediction. SnapKin is freely available at https://github.com/PYangLab/SnapKin.

Mitochondrial electron transport chain, ceramide and Coenzyme Q are linked in a pathway that drives insulin resistance in skeletal muscle.

Insulin resistance (IR) is a complex metabolic disorder that underlies several human diseases, including type 2 diabetes and cardiovascular disease. Despite extensive research, the precise mechanisms underlying IR development remain poorly understood. Here, we provide new insights into the mechanistic connections between cellular alterations associated with IR, including increased ceramides, deficiency of coenzyme Q (CoQ), mitochondrial dysfunction, and oxidative stress. We demonstrate that elevated levels of ceramide in the mitochondria of skeletal muscle cells results in CoQ depletion and loss of mitochondrial respiratory chain components, leading to mitochondrial dysfunction and IR. Further, decreasing mitochondrial ceramide levels in vitro and in animal models (under chow and high fat diet) increased CoQ levels and was protective against IR. CoQ supplementation also rescued ceramide-associated IR. Examination of the mitochondrial proteome from human muscle biopsies revealed a strong correlation between the respirasome system and mitochondrial ceramide as key determinants of insulin sensitivity. Our findings highlight the mitochondrial Ceramide-CoQ-respiratory chain nexus as a potential foundation of an IR pathway that may also play a critical role in other conditions associated with ceramide accumulation and mitochondrial dysfunction, such as heart failure, cancer, and aging. These insights may have important clinical implications for the development of novel therapeutic strategies for the treatment of IR and related metabolic disorders.

Phosphoproteomics reveals rewiring of the insulin signaling network and multi-nodal defects in insulin resistance.

The failure of metabolic tissues to appropriately respond to insulin ("insulin resistance") is an early marker in the pathogenesis of type 2 diabetes. Protein phosphorylation is central to the adipocyte insulin response, but how adipocyte signaling networks are dysregulated upon insulin resistance is unknown. Here we employ phosphoproteomics to delineate insulin signal transduction in adipocyte cells and adipose tissue. Across a range of insults causing insulin resistance, we observe a marked rewiring of the insulin signaling network. This includes both attenuated insulin-responsive phosphorylation, and the emergence of phosphorylation uniquely insulin-regulated in insulin resistance. Identifying dysregulated phosphosites common to multiple insults reveals subnetworks containing non-canonical regulators of insulin action, such as MARK2/3, and causal drivers of insulin resistance. The presence of several bona fide GSK3 substrates among these phosphosites led us to establish a pipeline for identifying context-specific kinase substrates, revealing widespread dysregulation of GSK3 signaling. Pharmacological inhibition of GSK3 partially reverses insulin resistance in cells and tissue explants. These data highlight that insulin resistance is a multi-nodal signaling defect that includes dysregulated MARK2/3 and GSK3 activity.

Deep Proteome Profiling of White Adipose Tissue Reveals Marked Conservation and Distinct Features Between Different Anatomical Depots.

White adipose tissue is deposited mainly as subcutaneous adipose tissue (SAT), often associated with metabolic protection, and abdominal/visceral adipose tissue, which contributes to metabolic disease. To investigate the molecular underpinnings of these differences, we conducted comprehensive proteomics profiling of whole tissue and isolated adipocytes from these two depots across two diets from C57Bl/6J mice. The adipocyte proteomes from lean mice were highly conserved between depots, with the major depot-specific differences encoded by just 3% of the proteome. Adipocytes from SAT (SAdi) were enriched in pathways related to mitochondrial complex I and beiging, whereas visceral adipocytes (VAdi) were enriched in structural proteins and positive regulators of mTOR presumably to promote nutrient storage and cellular expansion. This indicates that SAdi are geared toward higher catabolic activity, while VAdi are more suited for lipid storage. By comparing adipocytes from mice fed chow or Western diet (WD), we define a core adaptive proteomics signature consisting of increased extracellular matrix proteins and decreased fatty acid metabolism and mitochondrial Coenzyme Q biosynthesis. Relative to SAdi, VAdi displayed greater changes with WD including a pronounced decrease in mitochondrial proteins concomitant with upregulation of apoptotic signaling and decreased mitophagy, indicating pervasive mitochondrial stress. Furthermore, WD caused a reduction in lipid handling and glucose uptake pathways particularly in VAdi, consistent with adipocyte de-differentiation. By overlaying the proteomics changes with diet in whole adipose tissue and isolated adipocytes, we uncovered concordance between adipocytes and tissue only in the visceral adipose tissue, indicating a unique tissue-specific adaptation to sustained WD in SAT. Finally, an in-depth comparison of isolated adipocytes and 3T3-L1 proteomes revealed a high degree of overlap, supporting the utility of the 3T3-L1 adipocyte model. These deep proteomes provide an invaluable resource highlighting differences between white adipose depots that may fine-tune their unique functions and adaptation to an obesogenic environment.

A high-content endogenous GLUT4 trafficking assay reveals new aspects of adipocyte biology.

Insulin-induced GLUT4 translocation to the plasma membrane in muscle and adipocytes is crucial for whole-body glucose homeostasis. Currently, GLUT4 trafficking assays rely on overexpression of tagged GLUT4. Here we describe a high-content imaging platform for studying endogenous GLUT4 translocation in intact adipocytes. This method enables high fidelity analysis of GLUT4 responses to specific perturbations, multiplexing of other trafficking proteins and other features including lipid droplet morphology. Using this multiplexed approach we showed that Vps45 and Rab14 are selective regulators of GLUT4, but Trarg1, Stx6, Stx16, Tbc1d4 and Rab10 knockdown affected both GLUT4 and TfR translocation. Thus, GLUT4 and TfR translocation machinery likely have some overlap upon insulin-stimulation. In addition, we identified Kif13A, a Rab10 binding molecular motor, as a novel regulator of GLUT4 traffic. Finally, comparison of endogenous to overexpressed GLUT4 highlights that the endogenous GLUT4 methodology has an enhanced sensitivity to genetic perturbations and emphasises the advantage of studying endogenous protein trafficking for drug discovery and genetic analysis of insulin action in relevant cell types.

Trafficking regulator of GLUT4-1 (TRARG1) is a GSK3 substrate.

Trafficking regulator of GLUT4-1, TRARG1, positively regulates insulin-stimulated GLUT4 trafficking and insulin sensitivity. However, the mechanism(s) by which this occurs remain(s) unclear. Using biochemical and mass spectrometry analyses we found that TRARG1 is dephosphorylated in response to insulin in a PI3K/Akt-dependent manner and is a novel substrate for GSK3. Priming phosphorylation of murine TRARG1 at serine 84 allows for GSK3-directed phosphorylation at serines 72, 76 and 80. A similar pattern of phosphorylation was observed in human TRARG1, suggesting that our findings are translatable to human TRARG1. Pharmacological inhibition of GSK3 increased cell surface GLUT4 in cells stimulated with a submaximal insulin dose, and this was impaired following Trarg1 knockdown, suggesting that TRARG1 acts as a GSK3-mediated regulator in GLUT4 trafficking. These data place TRARG1 within the insulin signaling network and provide insights into how GSK3 regulates GLUT4 trafficking in adipocytes.

Akt phosphorylates insulin receptor substrate to limit PI3K-mediated PIP3 synthesis.

The phosphoinositide 3-kinase (PI3K)-Akt network is tightly controlled by feedback mechanisms that regulate signal flow and ensure signal fidelity. A rapid overshoot in insulin-stimulated recruitment of Akt to the plasma membrane has previously been reported, which is indicative of negative feedback operating on acute timescales. Here, we show that Akt itself engages this negative feedback by phosphorylating insulin receptor substrate (IRS) 1 and 2 on a number of residues. Phosphorylation results in the depletion of plasma membrane-localised IRS1/2, reducing the pool available for interaction with the insulin receptor. Together these events limit plasma membrane-associated PI3K and phosphatidylinositol (3,4,5)-trisphosphate (PIP3) synthesis. We identified two Akt-dependent phosphorylation sites in IRS2 at S306 (S303 in mouse) and S577 (S573 in mouse) that are key drivers of this negative feedback. These findings establish a novel mechanism by which the kinase Akt acutely controls PIP3 abundance, through post-translational modification of the IRS scaffold.

For the body to work properly, cells must constantly 'talk' to each other using signalling molecules. Receiving a chemical signal triggers a series of molecular events in a cell, a so-called 'signal transduction pathway' that connects a signal with a precise outcome. Disturbing cell signalling can trigger disease, and strict control mechanisms are therefore in place to ensure that communication does not break down or become erratic. For instance, just as a thermostat turns off the heater once the right temperature is reached, negative feedback mechanisms in cells switch off signal transduction pathways when the desired outcome has been achieved. The hormone insulin is a signal for growth that increases in the body following a meal to promote the storage of excess blood glucose (sugar) in muscle and fat cells. The hormone binds to insulin receptors at the cell surface and switches on a signal transduction pathway that makes the cell take up glucose from the bloodstream. If the signal is not engaged diseases such as diabetes develop. Conversely, if the signal cannot be adequately switched of cancer can develop. Determining exactly how insulin works would help to understand these diseases better and to develop new treatments. Kearney et al. therefore set out to examine the biochemical 'fail-safes' that control insulin signalling. Experiments using computer simulations of the insulin signalling pathway revealed a potential new mechanism for negative feedback, which centred on a molecule known as Akt. The models predicted that if the negative feedback were removed, then Akt would become hyperactive and accumulate at the cell's surface after stimulation with insulin. Further manipulation of the 'virtual' insulin signalling pathway and studies of live cells in culture confirmed that this was indeed the case. The cell biology experiments also showed how Akt, once at the cell surface, was able to engage the negative feedback and shut down further insulin signalling. Akt did this by inactivating a protein required to pass the signal from the insulin receptor to the rest of the cell. Overall, this work helps to understand cell communication by revealing a previously unknown, and critical component of the insulin signalling pathway.

Signaling Heterogeneity is Defined by Pathway Architecture and Intercellular Variability in Protein Expression.

Insulin's activation of PI3K/Akt signaling, stimulates glucose uptake by enhancing delivery of GLUT4 to the cell surface. Here we examined the origins of intercellular heterogeneity in insulin signaling. Akt activation alone accounted for ~25% of the variance in GLUT4, indicating that additional sources of variance exist. The Akt and GLUT4 responses were highly reproducible within the same cell, suggesting the variance is between cells (extrinsic) and not within cells (intrinsic). Generalized mechanistic models (supported by experimental observations) demonstrated that the correlation between the steady-state levels of two measured signaling processes decreases with increasing distance from each other and that intercellular variation in protein expression (as an example of extrinsic variance) is sufficient to account for the variance in and between Akt and GLUT4. Thus, the response of a population to insulin signaling is underpinned by considerable single-cell heterogeneity that is largely driven by variance in gene/protein expression between cells.

CASK modulates the assembly and function of the Mint1/Munc18-1 complex to regulate insulin secretion.

Calcium/calmodulin-dependent protein serine kinase (CASK) is a key player in vesicle transport and release in neurons. However, its precise role, particularly in nonneuronal systems, is incompletely understood. We report that CASK functions as an important regulator of insulin secretion. CASK depletion in mouse islets/ß cells substantially reduces insulin secretion and vesicle docking/fusion. CASK forms a ternary complex with Mint1 and Munc18-1, and this event is regulated by glucose stimulation in ß cells. The crystal structure of the CASK/Mint1 complex demonstrates that Mint1 exhibits a unique "whip"-like structure that wraps tightly around the CASK-CaMK domain, which contains dual hydrophobic interaction sites. When triggered by CASK binding, Mint1 modulates the assembly of the complex. Further investigation revealed that CASK-Mint1 binding is critical for ternary complex formation, thereby controlling Munc18-1 membrane localization and insulin secretion. Our work illustrates the distinctive molecular basis underlying CASK/Mint1/Munc18-1 complex formation and reveals the importance of the CASK-Mint1-Munc18 signaling axis in insulin secretion.

Regulation of hepatic insulin signaling and glucose homeostasis by sphingosine kinase 2.

Sphingolipid dysregulation is often associated with insulin resistance, while the enzymes controlling sphingolipid metabolism are emerging as therapeutic targets for improving insulin sensitivity. We report herein that sphingosine kinase 2 (SphK2), a key enzyme in sphingolipid catabolism, plays a critical role in the regulation of hepatic insulin signaling and glucose homeostasis both in vitro and in vivo. Hepatocyte-specific Sphk2 knockout mice exhibit pronounced insulin resistance and glucose intolerance. Likewise, SphK2-deficient hepatocytes are resistant to insulin-induced activation of the phosphoinositide 3-kinase (PI3K)-Akt-FoxO1 pathway and elevated hepatic glucose production. Mechanistically, SphK2 deficiency leads to the accumulation of sphingosine that, in turn, suppresses hepatic insulin signaling by inhibiting PI3K activation in hepatocytes. Either reexpressing functional SphK2 or pharmacologically inhibiting sphingosine production restores insulin sensitivity in SphK2-deficient hepatocytes. In conclusion, the current study provides both experimental findings and mechanistic data showing that SphK2 and sphingosine in the liver are critical regulators of insulin sensitivity and glucose homeostasis.

Mitochondrial oxidants, but not respiration, are sensitive to glucose in adipocytes.

Insulin action in adipose tissue is crucial for whole-body glucose homeostasis, with insulin resistance being a major risk factor for metabolic diseases such as type 2 diabetes. Recent studies have proposed mitochondrial oxidants as a unifying driver of adipose insulin resistance, serving as a signal of nutrient excess. However, neither the substrates for nor sites of oxidant production are known. Because insulin stimulates glucose utilization, we hypothesized that glucose oxidation would fuel respiration, in turn generating mitochondrial oxidants. This would impair insulin action, limiting further glucose uptake in a negative feedback loop of "glucose-dependent" insulin resistance. Using primary rat adipocytes and cultured 3T3-L1 adipocytes, we observed that insulin increased respiration, but notably this occurred independently of glucose supply. In contrast, glucose was required for insulin to increase mitochondrial oxidants. Despite rising to similar levels as when treated with other agents that cause insulin resistance, glucose-dependent mitochondrial oxidants failed to cause insulin resistance. Subsequent studies revealed a temporal relationship whereby mitochondrial oxidants needed to increase before the insulin stimulus to induce insulin resistance. Together, these data reveal that (a) adipocyte respiration is principally fueled from nonglucose sources; (b) there is a disconnect between respiration and oxidative stress, whereby mitochondrial oxidant levels do not rise with increased respiration unless glucose is present; and (c) mitochondrial oxidative stress must precede the insulin stimulus to cause insulin resistance, explaining why short-term, insulin-dependent glucose utilization does not promote insulin resistance. These data provide additional clues to mechanistically link nutrient excess to adipose insulin resistance.

Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis.

BACKGROUND: Single-cell RNA-sequencing (scRNA-seq) is a transformative technology, allowing global transcriptomes of individual cells to be profiled with high accuracy. An essential task in scRNA-seq data analysis is the identification of cell types from complex samples or tissues profiled in an experiment. To this end, clustering has become a key computational technique for grouping cells based on their transcriptome profiles, enabling subsequent cell type identification from each cluster of cells. Due to the high feature-dimensionality of the transcriptome (i.e. the large number of measured genes in each cell) and because only a small fraction of genes are cell type-specific and therefore informative for generating cell type-specific clusters, clustering directly on the original feature/gene dimension may lead to uninformative clusters and hinder correct cell type identification. RESULTS: Here, we propose an autoencoder-based cluster ensemble framework in which we first take random subspace projections from the data, then compress each random projection to a low-dimensional space using an autoencoder artificial neural network, and finally apply ensemble clustering across all encoded datasets to generate clusters of cells. We employ four evaluation metrics to benchmark clustering performance and our experiments demonstrate that the proposed autoencoder-based cluster ensemble can lead to substantially improved cell type-specific clusters when applied with both the standard k-means clustering algorithm and a state-of-the-art kernel-based clustering algorithm (SIMLR) designed specifically for scRNA-seq data. Compared to directly using these clustering algorithms on the original datasets, the performance improvement in some cases is up to 100%, depending on the evaluation metric used. CONCLUSIONS: Our results suggest that the proposed framework can facilitate more accurate cell type identification as well as other downstream analyses. The code for creating the proposed autoencoder-based cluster ensemble framework is freely available from https://github.com/gedcom/scCCESS.

Global redox proteome and phosphoproteome analysis reveals redox switch in Akt.

Protein oxidation sits at the intersection of multiple signalling pathways, yet the magnitude and extent of crosstalk between oxidation and other post-translational modifications remains unclear. Here, we delineate global changes in adipocyte signalling networks following acute oxidative stress and reveal considerable crosstalk between cysteine oxidation and phosphorylation-based signalling. Oxidation of key regulatory kinases, including Akt, mTOR and AMPK influences the fidelity rather than their absolute activation state, highlighting an unappreciated interplay between these modifications. Mechanistic analysis of the redox regulation of Akt identified two cysteine residues in the pleckstrin homology domain (C60 and C77) to be reversibly oxidized. Oxidation at these sites affected Akt recruitment to the plasma membrane by stabilizing the PIP3 binding pocket. Our data provide insights into the interplay between oxidative stress-derived redox signalling and protein phosphorylation networks and serve as a resource for understanding the contribution of cellular oxidation to a range of diseases.